Glassdoor Scraper — Company Reviews, Ratings, Interviews & Employer Leads

Extract complete Glassdoor company data — the full employee review history (every sub-rating, pros, cons, advice and the employer's own replies), the company rating breakdown (overall + six sub-ratings + CEO approval, recommend-to-friend and business-outlook percentages + the full 1–5 star distribution), interview experiences with the exact questions asked, and ready-to-contact employer leads. One clean dataset, every field other scrapers leave blank.

No login, no cookies, no browser — fast JSON extraction straight from Glassdoor's own data APIs, with a built-in monitor mode that pulls only new reviews on each run.

Why this Glassdoor scraper?

Most Glassdoor scrapers grab the first few review pages and stop, or return only review text with none of the structured ratings. This actor reads Glassdoor's internal review & interview APIs directly and ships the richest dataset in the category — four record types, every sub-rating, employer replies, and pagination that goes all the way through the review history (no anonymous cap).

Data	Typical scrapers	This actor
Overall rating + review text	✅	✅
All six sub-ratings (work-life, culture, comp & benefits, career, senior leadership, diversity)	❌	✅
Recommend-to-friend / CEO-approval / business-outlook verdicts (per review and company-wide %)	❌	✅
Pros, cons and advice to management	partial	✅
Employer's official responses to reviews	❌	✅
Current vs former employee, job title, location, tenure	partial	✅
Helpful / not-helpful counts per review	❌	✅
Full company rating distribution (how many 1★…5★)	❌	✅
Interview difficulty, experience, outcome, process and the questions asked	❌	✅
Employer leads with website, reputation & 0–100 lead score	❌	✅
Website-crawled contact emails / phones / socials	❌	✅ opt-in
Pagination through the entire review history	❌	✅
Monitor mode — only new reviews per run	❌	✅

Use cases

• Employer-reputation & brand monitoring — track a company's overall rating, CEO approval, recommend-to-friend % and the flow of new reviews over time. Perfect for HR, talent-brand and PR teams watching their own (or a competitor's) Glassdoor presence.
• Competitive & market intelligence — benchmark culture, work-life balance, comp & benefits and management scores across a set of companies in one dataset.
• Recruiting & candidate research — pull interview experiences, difficulty and the actual questions asked to brief candidates or design hiring loops.
• Investment & due diligence — employee sentiment, rating trends and management approval are leading indicators analysts and acquirers track.
• B2B lead generation — every company becomes a scored employer lead (firmographics + reputation + website contacts) for HR-tech, recruiting, employer-branding, comp-benchmarking and engagement-survey vendors.

How to use

1. Sign up for Apify — the free plan is enough to try this actor.
2. Open the Glassdoor Scraper, enter company names (or paste Glassdoor company URLs), choose what to scrape, and click Start.
3. Watch results stream into the dataset table — switch between the Companies / Reviews / Interviews / Employer leads views.
4. Export as JSON, CSV, Excel, XML or RSS — or pull results programmatically via the Apify API.

Input

{
    "companyNames": ["Google", "Netflix"],
    "includeCompanyOverview": true,
    "includeReviews": true,
    "includeInterviews": true,
    "maxReviews": 200,
    "reviewsSort": "recent",
    "outputEmployerLeads": true,
    "enrichLeadEmails": true,
    "monitorMode": false
}

• companyNames — look companies up by name; each is resolved to its Glassdoor employer page automatically.
• startUrls — paste Glassdoor company URLs instead (any tab works: Overview, Reviews, Interviews, Salary, Jobs). More precise when several employers share a name.
• employerIds — numeric Glassdoor employer IDs (the number after -E / EI_IE in a company URL), e.g. 9079 for Google.
• includeCompanyOverview (default true) — one company record per employer: overall rating, all six sub-ratings, CEO approval %, recommend-to-friend %, business-outlook %, the full 1–5 star distribution and review count.
• includeReviews (default true) — employee reviews with every sub-rating, verdicts, pros/cons/advice, job title, location, tenure, helpful counts and employer replies.
• includeInterviews (default false) — interview difficulty, experience, outcome, full process description, negotiation notes and the exact questions asked.
• outputEmployerLeads (default false) — one scored employer-lead record per company (firmographics + reputation + 0–100 lead score).
• enrichLeadEmails (default false) — crawl each company's own website for public contact emails, phones and socials. Glassdoor never exposes emails — this is the only way to get them.
• maxReviews / maxInterviews — caps per company (0 = all available).
• reviewsSort — recent (best for monitoring) or helpful. reviewLanguage — ISO-3 filter (eng, fra, …) or all. employmentStatus — all, current or former. reviewsStartDate — stop paging once reviews are older than this date (great for incremental pulls).
• monitorMode (default false) — emit only reviews/interviews not seen in previous runs.

Output

One record per type — company, review, interview and employerLead:

{
    "type": "review",
    "employerId": "9079",
    "companyName": "Google",
    "reviewId": "104451973",
    "reviewUrl": "https://www.glassdoor.com/Reviews/Employee-Review-Google-E9079-RVW104451973.htm",
    "reviewDateTime": "2026-06-18T22:43:17.023",
    "summary": "Great place to grow",
    "pros": "Smart people, strong comp, real work-life balance.",
    "cons": "Large org — decisions can be slow.",
    "advice": "Keep investing in internal mobility.",
    "ratingOverall": 5,
    "ratingWorkLifeBalance": 4,
    "ratingCultureAndValues": 5,
    "ratingCompensationAndBenefits": 5,
    "ratingCareerOpportunities": 4,
    "recommendToFriend": "RECOMMEND",
    "ceoRating": "APPROVE",
    "employmentStatus": "REGULAR",
    "isCurrentEmployee": true,
    "jobTitle": "Software Engineer",
    "reviewerLocation": "Mountain View, CA",
    "lengthOfEmploymentYears": 3,
    "countHelpful": 12,
    "employerResponses": [],
    "scrapedAt": "2026-06-19T23:00:30.000Z"
}

{
    "type": "company",
    "employerId": "9079",
    "companyName": "Google",
    "website": "https://www.google.com",
    "glassdoorUrl": "https://www.glassdoor.com/Overview/Working-at-Google-EI_IE9079.htm",
    "overallRating": 4.4,
    "reviewCount": 70268,
    "ratingWorkLifeBalance": 4.2,
    "ratingCompensationAndBenefits": 4.5,
    "ratingCultureAndValues": 4.3,
    "recommendToFriendPercent": 87,
    "ceoApprovalPercent": 83,
    "businessOutlookPercent": 81,
    "ceoName": "Sundar Pichai",
    "ratingDistribution": { "oneStar": 472, "twoStar": 489, "threeStar": 2042, "fourStar": 5773, "fiveStar": 11519 }
}

Interview records add difficulty, experience, outcome, processDescription, negotiationDescription and an interviewQuestions array. Employer-lead records add emails, phones, socials and a leadScore.

Automate & schedule

Run this actor on autopilot and pull results into your own stack:

• Apify API — start runs, fetch datasets, and manage schedules over REST.
• apify-client for JavaScript and apify-client for Python — official SDKs.
• Schedules — run it daily/weekly with monitor mode on to capture only new reviews; the Schedule decides when to run, monitor mode decides which items are new — they never conflict.
• Webhooks — trigger downstream actions (CRM import, Slack alert, BI refresh) the moment a run finishes.

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'MY_APIFY_TOKEN' });

const run = await client.actor('scrapesage/glassdoor-scraper').call({
    companyNames: ['Google', 'Netflix'],
    includeReviews: true,
    includeInterviews: true,
    maxReviews: 200,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Got ${items.length} companies, reviews & interviews`);

Integrate with any app

Connect the dataset to 5,000+ apps — no code required:

• Make — multi-step automation scenarios.
• Zapier — push new reviews or employer leads straight into your CRM or a Slack channel.
• Slack — get notified when a monitored company gets new reviews.
• Google Drive / Sheets — auto-export every run to a spreadsheet.
• Airbyte — pipe results into your data warehouse.
• GitHub — trigger runs from commits or releases.

Use with AI assistants (MCP)

The output is clean, LLM-ready JSON. Call this actor from Claude, ChatGPT or any agent framework through the Apify MCP server — ask your assistant to "pull Google's latest Glassdoor reviews and summarise the sentiment" and let it run this scraper for you.

Agent-ready: autonomous payments (x402 & Skyfire)

This actor is agent-ready — AI agents can discover it, run it, and pay for it autonomously, with no Apify account and no human in the loop. It uses pay-per-event pricing and limited permissions, so it qualifies for Apify's agentic-payment standards:

• x402 — an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the Apify MCP server — no account, no API key.
• Skyfire — agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

More scrapers from scrapesage

Build a complete hiring, employer-brand & compensation intelligence stack:

• Levels.fyi Scraper — tech salaries, total compensation & leveling by company.
• Talent.com Jobs Scraper — global job listings with real salaries and employer leads.
• Seek Job Scraper — Australia & New Zealand jobs, salaries & company data.
• LinkedIn Jobs Scraper — job postings as hiring-intent signals.
• GitHub Scraper — developers, repos & org data for technical recruiting.
• Stack Overflow & Stack Exchange Scraper — Q&A and developer leads.
• Website Contact Scraper — turn any domain list into emails, phones & socials.

Tips

• Big employers: Glassdoor exposes the entire review history (Google has 70,000+ reviews). Set maxReviews to a sensible cap, or use reviewsStartDate + reviewsSort: recent for incremental pulls.
• Incremental feeds: combine Schedules with monitorMode to capture only new reviews each run.
• Proxies: keep the default US residential proxy group — Glassdoor sits behind Cloudflare and blocks datacenter IPs.
• Cost control: scrape a single record type (e.g. reviews only) for one clean, fully-populated table, and enable enrichLeadEmails only when you need contacts.

FAQ

How do I scrape reviews for a specific company? Put its name in companyNames (e.g. Google) or paste any Glassdoor company URL into startUrls. The actor resolves the employer automatically.

Does it work without logging in? Yes — no Glassdoor account, cookies or browser needed. The actor reads Glassdoor's public review and interview data directly.

Can it get all the reviews, past the usual limit? Yes. Unlike anonymous browsing, this actor paginates through the full review history; set maxReviews: 0 to collect everything.

Can I export to Google Sheets, CSV or Excel? Yes — one click in the dataset view, or automatically on every run via the Google Drive integration.

How do I monitor new reviews automatically? Turn on monitorMode and create a Schedule (e.g. daily). Only reviews/interviews new since the last run are emitted — ideal for alerts and dashboards.

Where do the emails come from? Never from Glassdoor (it doesn't publish them). With enrichLeadEmails on, the actor visits the company's own public website and extracts publicly listed contact details — the same thing a human visitor would see.

Is scraping Glassdoor legal? This actor collects publicly available data only. You are responsible for using the data in compliance with applicable laws (GDPR/CCPA for personal data) and Glassdoor's terms.

A field is empty — why? Some reviews genuinely don't include every sub-rating, advice, or an employer response, and some companies don't publish contact emails. Fields are omitted only when the data doesn't exist, not because the scraper skipped them.

Need help?

Open an issue on the actor's Issues tab, or visit the Apify help center. Feature requests are welcome — this actor is actively maintained.